Monitoring dry vegetation masses in semi-arid areas with MODIS SWIR bands
Monitoring dry vegetation masses in semi-arid areas with MODIS SWIR bands
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DOI：
10.1016/j.rse.2014.07.027
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发表时间：
2014-10
影响因子：
13.5
通讯作者：
D. Jacques;L. Kergoat;P. Hiernaux;E. Mougin;P. Defourny
中科院分区：
文献类型：
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作者：
D. Jacques;L. Kergoat;P. Hiernaux;E. Mougin;P. Defourny
监测半干旱地区旱季草本植被的质量对于生态学、农学或经济的一些领域很重要，遥感为此提供了相关的空间覆盖范围和频率。现有的遥感研究致力于干草本植被检测主要是出于土壤耕作强度和土壤残留物管理，土壤侵蚀的风险，野火的风险与死燃料的质量的评估。到目前为止，很少有研究涉及监测大面积旱季期间秸秆和垃圾的退化情况，而它们是牲畜可持续性的重要饲料。2004年至2011年，在萨赫勒地区对20多个牧场进行了实地测量，对中分辨率成像光谱仪波段组合（NBAR收集5）进行了测试。利用中分辨率成像光谱仪短波红外波段（波段6以1.6μm为中心，波段7以2.1μm为中心），特别是土壤耕作指数（STI），获得了指数的最佳经验线性模型。STI解释了旱季和中间季节数据干物质方差的66%（质量= 3158（STI-1.05），r2= 0.66，RMSE = 280 kg DM/ha，n = 232）。还建议对全年数据进行回归（质量= 3371（STI-1.06），r2= 0.67，RMSE = 352千克干物质/公顷，n = 536）。很好地捕捉到了强烈的站点间和年际变化，并发现衰减率与放牧强度和火灾发生一致。结果表明，STI可以应用于监测质量的干组织在萨赫勒地区，并可能在许多半干旱地区。
Monitoring the mass of herbaceous vegetation during the dry season in semi-arid areas is important for a number of domains in ecology, agronomy, or economy and remote sensing offers relevant spatial coverage and frequency to that end. Existing remote sensing studies dedicated to dry herbaceous vegetation detection are mainly motivated by the assessment of soil tillage intensity and soil residue management, risk of soil erosion, and risk of wildfire linked to the mass of dead fuel. Few studies so far have dealt with monitoring of straw and litter degradation during the dry season over large areas while they are important fodder for livestock sustainability. MODIS band combinations (NBAR collection 5) were tested against a set of field measurements carried out over 20 rangeland sites from 2004 to 2011 in the Sahel. The best empirical linear models were obtained for indices using MODIS bands in the shortwave infrared domain (Band 6 centered at 1.6μm, Band 7 centered at 2.1μm), in particular with the Soil Tillage Index (STI). STI explained 66% of the variance of dry masses (Mass= 3158(STI − 1.05), r2= 0.66, RMSE = 280 kg DM/ha, n = 232) for dry and intermediate season data. A regression is also proposed for year-round data (Mass= 3371(STI − 1.06), r2= 0.67, RMSE = 352 kg DM/ha, n = 536). The strong inter-site and inter-annual variabilitieswere well captured and the decay rate was found consistent with grazing intensity and fire occurrence. The results imply that the STI can be applied to monitor the mass of dry tissues in the Sahel and potentially in many semi-arid areas.